1. Field of the Invention
The present invention relates to the field of computer graphics and, in particular, to a system and method for invariant-based normal estimation.
2. Description of the Related Art
Recently there has been an increasing demand for three-dimensional (3D) face models. The movie industry relies more and more on computer graphics (CG) to place human actors in situations that are physically not feasible. In some situations, the actor is completely replaced by a corresponding virtual counterpart since the required shots would endanger the actor.
To integrate the actors or their CG representations seamlessly, light and shadows cast from other objects must be matched. Conventional approaches using coarse facial models are not sufficient since the human eye is trained to read faces, so even subtle imperfections are spotted immediately. Also, secondary effects, such as wrinkle formation, are especially hard and tedious to create for an animator, but these secondary effects are essential for natural face appearance.
Physical simulation is currently being investigated for facial capture but is very difficult to implement since the human face is a highly complex and non-linear structure. Currently, the only practical option is to acquire a model of the face using 3D capture. The acquired models can be either integrated directly into a movie or can be used to control other faces. In addition, the movie industry is not the only industry that demands realistic face models. Computer games have a demand for virtual characters. Also, medical science has an interest in such models.
Conventional approaches to 3D capture may be classified as either depth estimation techniques or normal estimation techniques. The depth variation of mesoscopic skin details, such as pores and wrinkles, is in the micrometer range. Most depth estimation techniques simply cannot achieve that level of detail with current hardware. Laser scanning is capable of recovering depth variations at these scales, but this technology produces insufficient results because of the translucency of skin. As a workaround, a plaster mold of the face is scanned instead. Each of these depth estimation techniques suffers from various drawbacks, including the cumbersome process of obtaining a plaster mold of the actor's face.
Normal estimation techniques distinguish between diffuse and specular normals that emanate from the surface of an object. Conventional techniques for normal estimation are based on polarization. The polarization-based normal estimation techniques separate the specular component explicitly from the diffuse component, which is only possible with the use of polarization. However, polarization-based normal estimation has some major drawbacks, since it is restricted to a single viewpoint and reduces the useable light drastically. Furthermore, optical elements such as beam-splitters are very sensitive, thus the whole apparatus has to be handled with care.
As the foregoing illustrates, there is a need in the art for an improved technique for capture of high-resolution models, such as high-resolution face models.